Evaluating AI deployments and machine learning based on overall energy usage instead of just processing power is a new idea. It’s so new that there is no standard metric currently. Each section of the ML pipeline consumes an enormous amount of energy, and each section should be evaluated and enhanced.
-
-
Articles récents
- Intel® Xeon® Processors: The Most Preferred CPU for AI Host Nodes
- Building AI With Empathy: Sorenson’s Mission for Accessibility
- Multi-node deployments using Intel® AI for Enterprise RAG
- Connected Data is the Future: How Neo4j Is Enabling the Next Generation of AI
- Orchestrating AI for Real Business Value: Google Cloud’s Approach to Scalable Intelligence
-
Neural networks news
Intel NN News
- Intel® Xeon® Processors: The Most Preferred CPU for AI Host Nodes
Today’s AI workloads are not purely offloaded to GPU accelerators. Host CPUs such as the Intel® […]
- Multi-node deployments using Intel® AI for Enterprise RAG
As enterprises scale generative AI across diverse infrastructures, Intel® AI for Enterprise RAG […]
- Building AI With Empathy: Sorenson’s Mission for Accessibility
For Sorenson Senior Director of AI Mariam Rahmani, the future of AI isn’t about building the […]
- Intel® Xeon® Processors: The Most Preferred CPU for AI Host Nodes
-